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11:56 AM, December 7, 2017
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DARPA's 'Ocean of things' illustration: Image by DARPA

The US Defence Advnced Reasearch Projects Agency (DARPA) Wednesday announced its Ocean of Things program, to enable situational awareness over oceans by deploying thousands of small floats that could form a distributed sensor network.

Each smart float would contain a suite of commercially available sensors to collect environmental data—such as ocean temperature, sea state, and location—as well as activity data about commercial vessels, aircraft, and even maritime mammals moving through the area.

The floats would transmit data periodically via satellite to a cloud network for storage and real-time analysis.

John Waterston, program manager in DARPA’s Strategic Technology Office (STO) said in a statement, “By coupling powerful analytical tools with commercial sensor technology, we plan to create floating sensor networks that significantly expand maritime awareness at a fraction of the cost of current approaches.”

The technical challenge for Ocean of Things lies in two key areas: float development and data analytics.

A Proposers Day is scheduled for January 4, 2018, in Arlington, Virginia, at the DARPA Conference Center.

Under float development, proposers must design an intelligent float to house a passive sensor suite that can survive in harsh maritime environments. Each float would report information from its surroundings for at least one year before safely scuttling itself in the deep ocean.

The floats will be required to be made of environmentally safe materials, pose no danger to vessels, and comply with all federal laws, regulations, and executive orders related to protection of marine life.

The data analytics portion of the Ocean of Things program will require proposers to develop cloud-based software and analytic techniques to process the floats’ reported data.

This effort includes dynamic display of float locations, health, and mission performance; processing of environmental data for oceanographic and meteorological models; developing algorithms to automatically detect, track, and identify nearby vessels; and identification of new indicators of maritime activity.

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